Along with development in IT infrastructures for persons/in companies, a huge amount of multimedia data (such as documents, videos/images, voices, or various log data) has been stored in large storages. In order to extract information efficiently from vast amount of stored data, various information search techniques for individual media data have been invented and put into practical use.
As an example of information search with respect to multimedia data, a method may be assumed for detecting objects or specific regions included in images. Object detection or region identification in images correspond to morphological analysis in document analysis (means for separating documents into words to determine word classes), which are important in analyzing meanings of images.
As a method for detecting objects in images, the method of Non Patent Literature 1 is commonly known, and is commercialized as face region detecting function in digital cameras or in monitoring systems. In the method of Non Patent Literature 1, vast amount of image samples of the detection target is collected, and multiple of discriminators on the basis of image brightness are generated by machine learning. These discriminators are combined to generate a determinator for partial regions of the image. The object region is identified by thoroughly searching the partial regions in the image.
The detection targets are usually human faces currently. However, if wide ranges of contents stored in storages are the detection targets, it is desired to detect various objects such as cars, animals, buildings, diagrams, or various goods. In addition, in order to process huge size data, it is required to improve efficiency of analysis process.
Regarding improvement in efficiency of analysis process, Patent Literature 1 listed below describes a method for utilizing existence probability of objects, thereby limiting the region to which image processing for detecting object regions is performed. The method of Patent Literature 1 utilizes static information of imaging system such as focal point distance or resolution, thereby determining regions to which image processing is performed. It may be advantageous in environments where imaging environments or imaging devices are limited such as in-vehicle cameras and where structured data is managed.